Dataset Information

Soluble Axl is an accurate biomarker of cirrhosis and hepatocellular carcinoma development: results from a large scale multicenter analysis.

ABSTRACT: Patients with chronic liver disease (CLD) and cirrhosis are at high risk for hepatocellular carcinoma (HCC). Current diagnostic tools for HCC detection include imaging techniques and serum biomarkers such as ?-fetoprotein (AFP). Yet, these methods are limited in sensitivity and specificity to accurately detect early HCC. Here we focused on the potential of soluble Axl (sAxl) as a biomarker in CLD patients by analyzing serum samples of 1067 patients and healthy controls from centers in Europe and Asia. We show that serum concentrations of sAxl were significantly increased at early (82.57 ng/mL) and later stages of HCC (114.50 ng/mL) as compared to healthy controls (40.15 ng/mL). Notably, no elevated sAxl levels were detected in patients with CLD including chronic viral hepatitis, autoimmune hepatitis, cholestatic liver disease, or non-alcoholic fatty liver disease versus healthy controls. Furthermore, sAxl did not rise in liver adenomas or cholangiocarcinoma (CCA). Yet, patients with advanced fibrosis (F3) or cirrhosis (F4) showed enhanced sAxl concentrations (F3: 54.67 ng/mL; F4: 94.74 ng/mL). Hepatic myofibroblasts exhibited an increased release of sAxl, suggesting that elevated sAxl levels arise from these cells during fibrosis. Receiver operating characteristic curve analysis of sAxl displayed a strongly increased sensitivity and specificity to detect both cirrhosis (80.8%/92.0%) and HCC (83.3%/86.7%) with an area under the curve of 0.935/0.903 as compared to AFP. In conclusion, sAxl shows high diagnostic accuracy at early stage HCC as well as cirrhosis, thereby outperforming AFP. Importantly, sAxl remains normal in most common CLDs, liver adenomas and CCA.

SUBMITTER: Dengler M

PROVIDER: S-EPMC5542263 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Soluble Axl is an accurate biomarker of cirrhosis and hepatocellular carcinoma development: results from a large scale multicenter analysis.

Dengler Mirko M Staufer Katharina K Huber Heidemarie H Stauber Rudolf R Bantel Heike H Weiss Karl Heinz KH Starlinger Patrick P Pock Hannelore H Klöters-Plachky Petra P Gotthardt Daniel N DN Rauch Peter P Lackner Carolin C Stift Judith J Brostjan Christine C Gruenberger Thomas T Kumada Takashi T Toyoda Hidenori H Tada Toshifumi T Weiss Thomas S TS Trauner Michael M Mikulits Wolfgang W

Oncotarget 20170701 28

Patients with chronic liver disease (CLD) and cirrhosis are at high risk for hepatocellular carcinoma (HCC). Current diagnostic tools for HCC detection include imaging techniques and serum biomarkers such as α-fetoprotein (AFP). Yet, these methods are limited in sensitivity and specificity to accurately detect early HCC. Here we focused on the potential of soluble Axl (sAxl) as a biomarker in CLD patients by analyzing serum samples of 1067 patients and healthy controls from centers in Europe and ...[more]

PMID: 28526812

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Project description:Hepatocellular carcinoma (HCC) is the third most lethal cancer worldwide. The lack of effective biomarkers for the early detection of HCC results in unsatisfactory curative treatments. Here, metabolite biomarkers were identified and validated for HCC diagnosis. A total of 1,448 subjects, including healthy controls and patients with chronic hepatitis B virus infection, liver cirrhosis, and HCC, were recruited from multiple centers in China. Liquid chromatography-mass spectrometry-based metabolomics methods were used to characterize the subjects' serum metabolic profiles and to screen and validate the HCC biomarkers. A serum metabolite biomarker panel including phenylalanyl-tryptophan and glycocholate was defined. This panel had a higher diagnostic performance than did α-fetoprotein (AFP) in differentiating HCC from a high-risk population of cirrhosis, such as an area under the receiver-operating characteristic curve of 0.930, 0.892, and 0.807 for the panel versus 0.657, 0.725, and 0.650 for AFP in the discovery set, test set, and cohort 1 of the validation set, respectively. In the nested case-control study, this panel had high sensitivity (range 80.0%-70.3%) to detect preclinical HCC, and its combination with AFP provided better risk prediction of preclinical HCC before clinical diagnosis. Besides, this panel showed a larger area under the receiver-operating characteristic curve than did AFP (0.866 versus 0.682) to distinguish small HCC, and 80.6% of the AFP false-negative patients with HCC were correctly diagnosed using this panel in the test set, which was corroborated by the validation set. The specificity and biological relevance of the identified biomarkers were further evaluated using sera from another two cancers and HCC tissue specimens, respectively. Conclusion: The discovered and validated serum metabolite biomarker panel exhibits good diagnostic performance for the early detection of HCC from at-risk populations. (Hepatology 2018;67:662-675).

Project description:The high mortality rate of hepatocellular carcinoma (HCC) is primarily due to its late diagnosis. In the past, numerous attempts have been made to design genetic biomarkers for the identification of HCC; unfortunately, most of the studies are based on small datasets obtained from a specific platform or lack reasonable validation performance on the external datasets. In order to identify a universal expression-based diagnostic biomarker panel for HCC that can be applicable across multiple platforms, we have employed large-scale transcriptomic profiling datasets containing a total of 2,316 HCC and 1,665 non-tumorous tissue samples. These samples were obtained from 30 studies generated by mainly four types of profiling techniques (Affymetrix, Illumina, Agilent, and High-throughput sequencing), which are implemented in a wide range of platforms. Firstly, we scrutinized overlapping 26 genes that are differentially expressed in numerous datasets. Subsequently, we identified a panel of three genes (FCN3, CLEC1B, and PRC1) as HCC biomarker using different feature selection techniques. Three-genes-based HCC biomarker identified HCC samples in training/validation datasets with an accuracy between 93 and 98%, Area Under Receiver Operating Characteristic curve (AUROC) in a range of 0.97 to 1.0. A reasonable performance, i.e., AUROC 0.91-0.96 achieved on validation dataset containing peripheral blood mononuclear cells, concurred their non-invasive utility. Furthermore, the prognostic potential of these genes was evaluated on TCGA-LIHC and GSE14520 cohorts using univariate survival analysis. This analysis revealed that these genes are prognostic indicators for various types of the survivals of HCC patients (e.g., Overall Survival, Progression-Free Survival, Disease-Free Survival). These genes significantly stratified high-risk and low-risk HCC patients (p-value <0.05). In conclusion, we identified a universal platform-independent three-genes-based biomarker that can predict HCC patients with high precision and also possess significant prognostic potential. Eventually, we developed a web server HCCpred based on the above study to facilitate scientific community (http://webs.iiitd.edu.in/raghava/hccpred/).

Dataset Information

Soluble Axl is an accurate biomarker of cirrhosis and hepatocellular carcinoma development: results from a large scale multicenter analysis.

Publications

Soluble Axl is an accurate biomarker of cirrhosis and hepatocellular carcinoma development: results from a large scale multicenter analysis.

Similar Datasets

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